A neural network approach to high performance analog circuit design
In order to gain new insight into the design of high-precision, high-speed analog circuits, several possible network implementations of an A/D converter are presented. These networks are marked by programmability and parallelism, which can be used to maintain circuit precision without the use of feedback. This removes design constraints on closed-loop stability, and may lead to faster circuit performance. On-chip training or calibration is likely to be necessary, but can be done in an offline mode, and thus may not hinder circuit speed significantly.
Midwest Symposium on Circuits and Systems
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